Evidence map›Paper›PMID 25253455›Full record

ArticleProceedings. Biological sciences2014

Two-phase importance sampling for inference about transmission trees.

Elina Numminen, Claire Chewapreecha, Jukka Sirén, Claudia Turner, Paul Turner, Stephen D Bentley, Jukka Corander

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Bayesian reconstruction of transmission trees from genetic sequences and uncertain infection times.Statistical applications in genetics and molecular biology · 2020
    Article
  4. Article
  5. Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2019
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Using genomics data to reconstruct transmission trees during disease outbreaks.Revue scientifique et technique (International Office of Epizootics) · 2016
    Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Elina NumminenDepartment of Mathematics and Statistics, University of Helsinki, PO Box 68, 00014 Helsinki, Finland elina.numminen@helsinki.fi.
Claire ChewapreechaThe Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK.
Jukka SirénDepartment of Biosciences, University of Helsinki, PO Box 56, 00014 Helsinki, Finland.
Claudia TurnerShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sod, Thailand Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Paul TurnerShoklo Malaria Research Unit, Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Mae Sod, Thailand Centre for Tropical Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Stephen D BentleyDepartment of Biosciences, University of Helsinki, PO Box 56, 00014 Helsinki, Finland Department of Medicine, University of Cambridge, Addenbrookes Hospital, Cambridge CB2 0QQ, UK.
Jukka CoranderDepartment of Mathematics and Statistics, University of Helsinki, PO Box 68, 00014 Helsinki, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There has been growing interest in the statistics community to develop methods for inferring transmission pathways of infectious pathogens from molecular sequence data. For many datasets, the computational challenge lies in the huge dimension of the missing data. Here, we introduce an importance sampling scheme in which the transmission trees and phylogenies of pathogens are both sampled from reasonable importance distributions, alleviating the inference. Using this approach, arbitrary models of transmission could be considered, contrary to many earlier proposed methods. We illustrate the scheme by analysing transmissions of Streptococcus pneumoniae from household to household within a refugee camp, using data in which only a fraction of hosts is observed, but which is still rich enough to unravel the within-household transmission dynamics and pairs of households between whom transmission is plausible. We observe that while probability of direct transmission is low even for the most prominent cases of transmission, still those pairs of households are geographically much closer to each other than expected under random proximity.

Indexed as

Disease Transmission, InfectiousFamily CharacteristicsAdultBiometryDNA, BacterialFemaleHumansInfantMaleModels, TheoreticalMolecular Sequence DataPhylogenyPneumococcal InfectionsRefugeesStreptococcus pneumoniaeThailandDNA, Bacterialmolecular epidemiologyStreptococcus pneumoniatransmission tree

Identifiers

PMID25253455
PMCPMC4211445

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.